/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #pragma once #include #include #include // NOLINT #include #include #include // NOLINT #include #include #include "paddle/fluid/framework/data_feed.h" namespace paddle { namespace framework { // Dataset is a abstract class, which defines user interfaces // Example Usage: // Dataset* dataset = DatasetFactory::CreateDataset("InMemoryDataset") // dataset->SetFileList(std::vector{"a.txt", "b.txt"}) // dataset->SetThreadNum(1) // dataset->CreateReaders(); // dataset->SetDataFeedDesc(your_data_feed_desc); // dataset->LoadIntoMemory(); // dataset->SetTrainerNum(2); // dataset->GlobalShuffle(); class Dataset { public: Dataset() {} virtual ~Dataset() {} // set file list virtual void SetFileList(const std::vector& filelist) = 0; // set readers' num virtual void SetThreadNum(int thread_num) = 0; // set workers' num virtual void SetTrainerNum(int trainer_num) = 0; // set fleet send batch size virtual void SetFleetSendBatchSize(int64_t size) = 0; // set fs name and ugi virtual void SetHdfsConfig(const std::string& fs_name, const std::string& fs_ugi) = 0; // set data fedd desc, which contains: // data feed name, batch size, slots virtual void SetDataFeedDesc(const std::string& data_feed_desc_str) = 0; // set channel num virtual void SetChannelNum(int channel_num) = 0; // set merge by ins id virtual void SetMergeByInsId(const std::vector& merge_slot_list, bool erase_duplicate_feas, int min_merge_size, bool keep_unmerged_ins) = 0; // set fea eval mode virtual void SetFeaEval(bool fea_eval, int record_candidate_size) = 0; // get file list virtual const std::vector& GetFileList() = 0; // get thread num virtual int GetThreadNum() = 0; // get worker num virtual int GetTrainerNum() = 0; // get fleet send batch size virtual int64_t GetFleetSendBatchSize() = 0; // get hdfs config virtual std::pair GetHdfsConfig() = 0; // get data fedd desc virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() = 0; // get channel num virtual int GetChannelNum() = 0; // get readers, the reader num depend both on thread num // and filelist size virtual std::vector GetReaders() = 0; // create input channel and output channel virtual void CreateChannel() = 0; // register message handler between workers virtual void RegisterClientToClientMsgHandler() = 0; // load all data into memory virtual void LoadIntoMemory() = 0; // load all data into memory in async mode virtual void PreLoadIntoMemory() = 0; // wait async load done virtual void WaitPreLoadDone() = 0; // release all memory data virtual void ReleaseMemory() = 0; // local shuffle data virtual void LocalShuffle() = 0; // global shuffle data virtual void GlobalShuffle() = 0; // for slots shuffle virtual void SlotsShuffle(const std::set& slots_to_replace) = 0; virtual void GetRandomData(const std::set& slots_to_replace, std::vector* result) = 0; // create readers virtual void CreateReaders() = 0; // destroy readers virtual void DestroyReaders() = 0; // get memory data size virtual int64_t GetMemoryDataSize() = 0; // get shuffle data size virtual int64_t GetShuffleDataSize() = 0; // merge by ins id virtual void MergeByInsId() = 0; protected: virtual int ReceiveFromClient(int msg_type, int client_id, const std::string& msg) = 0; }; // DatasetImpl is the implementation of Dataset, // it holds memory data if user calls load_into_memory template class DatasetImpl : public Dataset { public: DatasetImpl(); virtual ~DatasetImpl() {} virtual void SetFileList(const std::vector& filelist); virtual void SetThreadNum(int thread_num); virtual void SetTrainerNum(int trainer_num); virtual void SetFleetSendBatchSize(int64_t size); virtual void SetHdfsConfig(const std::string& fs_name, const std::string& fs_ugi); virtual void SetDataFeedDesc(const std::string& data_feed_desc_str); virtual void SetChannelNum(int channel_num); virtual void SetMergeByInsId(const std::vector& merge_slot_list, bool erase_duplicate_feas, int min_merge_size, bool keep_unmerged_ins); virtual void SetFeaEval(bool fea_eval, int record_candidate_size); virtual const std::vector& GetFileList() { return filelist_; } virtual int GetThreadNum() { return thread_num_; } virtual int GetTrainerNum() { return trainer_num_; } virtual int64_t GetFleetSendBatchSize() { return fleet_send_batch_size_; } virtual std::pair GetHdfsConfig() { return std::make_pair(fs_name_, fs_ugi_); } virtual const paddle::framework::DataFeedDesc& GetDataFeedDesc() { return data_feed_desc_; } virtual int GetChannelNum() { return channel_num_; } virtual std::vector GetReaders(); virtual void CreateChannel(); virtual void RegisterClientToClientMsgHandler(); virtual void LoadIntoMemory(); virtual void PreLoadIntoMemory(); virtual void WaitPreLoadDone(); virtual void ReleaseMemory(); virtual void LocalShuffle(); virtual void GlobalShuffle(); virtual void SlotsShuffle(const std::set& slots_to_replace) {} virtual void GetRandomData(const std::set& slots_to_replace, std::vector* result) {} virtual void CreateReaders(); virtual void DestroyReaders(); virtual int64_t GetMemoryDataSize(); virtual int64_t GetShuffleDataSize(); virtual void MergeByInsId() {} protected: virtual int ReceiveFromClient(int msg_type, int client_id, const std::string& msg); std::vector> readers_; paddle::framework::Channel input_channel_; int channel_num_; std::vector> multi_output_channel_; std::vector> multi_consume_channel_; // when read ins, we put ins from one channel to the other, // and when finish reading, we set cur_channel = 1 - cur_channel, // so if cur_channel=0, all data are in output_channel, else consume_channel int cur_channel_; std::vector slots_shuffle_original_data_; RecordCandidateList slots_shuffle_rclist_; int thread_num_; paddle::framework::DataFeedDesc data_feed_desc_; int trainer_num_; std::vector filelist_; size_t file_idx_; std::mutex mutex_for_pick_file_; std::string fs_name_; std::string fs_ugi_; int64_t fleet_send_batch_size_; int64_t fleet_send_sleep_seconds_; std::vector preload_threads_; bool merge_by_insid_; bool erase_duplicate_feas_; bool keep_unmerged_ins_; int min_merge_size_; std::vector merge_slots_list_; bool slots_shuffle_fea_eval_ = false; }; // use std::vector or Record as data type class MultiSlotDataset : public DatasetImpl { public: MultiSlotDataset() {} virtual void MergeByInsId(); virtual void SlotsShuffle(const std::set& slots_to_replace); virtual void GetRandomData(const std::set& slots_to_replace, std::vector* result); virtual ~MultiSlotDataset() {} }; } // end namespace framework } // end namespace paddle